Evaluating Model-Driven Development for large-scale EHRs through the openEHR approach

Christensen, Bente; Ellingsen, Gunnar

doi:10.1016/j.ijmedinf.2016.02.004

Cited by 49 publications

(26 citation statements)

References 36 publications

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“…In EHR development there is a trend toward an openEHR approach. According to a longitudinal case study, key sociotechnical challenges to using the openEHR approach are the lack of technical and clinical competence in designing technical systems and modeling domains [8]. Developers and clinicians, therefore, need to work together in both arenas.…”

Section: Resultsmentioning

confidence: 99%

2016 Year-in-Review of Clinical and Consumer Informatics: Analysis and Visualization of Keywords and Topics

Park

Lee

et al. 2017

Healthc Inform Res

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ObjectivesThe objective of this study was to review and visualize the medical informatics field over the previous 12 months according to the frequencies of keywords and topics in papers published in the top four journals in the field and in Healthcare Informatics Research (HIR), an official journal of the Korean Society of Medical Informatics.MethodsA six-person team conducted an extensive review of the literature on clinical and consumer informatics. The literature was searched using keywords employed in the American Medical Informatics Association year-in-review process and organized into 14 topics used in that process. Data were analyzed using word clouds, social network analysis, and association rules.ResultsThe literature search yielded 370 references and 1,123 unique keywords. ‘Electronic Health Record’ (EHR) (78.6%) was the most frequently appearing keyword in the articles published in the five studied journals, followed by ‘telemedicine’ (2.1%). EHR (37.6%) was also the most frequently studied topic area, followed by clinical informatics (12.0%). However, ‘telemedicine’ (17.0%) was the most frequently appearing keyword in articles published in HIR, followed by ‘telecommunications’ (4.5%). Telemedicine (47.1%) was the most frequently studied topic area, followed by EHR (14.7%).ConclusionsThe study findings reflect the Korean government's efforts to introduce telemedicine into the Korean healthcare system and reactions to this from the stakeholders associated with telemedicine.

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Section: Resultsmentioning

confidence: 99%

2016 Year-in-Review of Clinical and Consumer Informatics: Analysis and Visualization of Keywords and Topics

Park

Lee

et al. 2017

Healthc Inform Res

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“…At the same time, the separation of clinical models from technical models (two-level modelling), which is one of the core openEHR solution constituents, will further foster effective software engineering by harnessing the benefits of model-driven development. Studies into this have varied in their findings, where some had positive insights about the effects of model-driven development in openEHR-based solutions [18] and others discovered challenges that still need to be solved in real world implementations [19]. …”

Section: Discussionmentioning

confidence: 99%

Applying openEHR’s Guideline Definition Language to the SITS international stroke treatment registry: a European retrospective observational study

Anani

Mazya

Chen

et al. 2017

BMC Med Inform Decis Mak

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BackgroundInteroperability standards intend to standardise health information, clinical practice guidelines intend to standardise care procedures, and patient data registries are vital for monitoring quality of care and for clinical research. This study combines all three: it uses interoperability specifications to model guideline knowledge and applies the result to registry data.MethodsWe applied the openEHR Guideline Definition Language (GDL) to data from 18,400 European patients in the Safe Implementation of Treatments in Stroke (SITS) registry to retrospectively check their compliance with European recommendations for acute stroke treatment.ResultsComparing compliance rates obtained with GDL to those obtained by conventional statistical data analysis yielded a complete match, suggesting that GDL technology is reliable for guideline compliance checking.ConclusionsThe successful application of a standard guideline formalism to a large patient registry dataset is an important step toward widespread implementation of computer-interpretable guidelines in clinical practice and registry-based research. Application of the methodology gave important results on the evolution of stroke care in Europe, important both for quality of care monitoring and clinical research.Electronic supplementary materialThe online version of this article (doi:10.1186/s12911-016-0401-5) contains supplementary material, which is available to authorized users.

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“…Two different trends can be seen. The first trend is going towards semantic-centered EHR rather than data-centered systems, such as developing EHR systems based on openEHR [192][193][194] or robust semantic encoding using semantic rich resources, such as SNOMED [195]. However, both approaches remain relatively marginal and resource intensive, though they most probably offer the better perspectives.…”

Section: H Clinical Practice and Research Integrationmentioning

confidence: 99%

Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress

Meystre¹,

Lovis²,

Bürkle³

et al. 2017

Yearb Med Inform

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SummaryObjective: To perform a review of recent research in clinical data reuse or secondary use, and envision future advances in this field. Methods: The review is based on a large literature search in MEDLINE (through PubMed), conference proceedings, and the ACM Digital Library, focusing only on research published between 2005 and early 2016. Each selected publication was reviewed by the authors, and a structured analysis and summarization of its content was developed. Results: The initial search produced 359 publications, reduced after a manual examination of abstracts and full publications. The following aspects of clinical data reuse are discussed: motivations and challenges, privacy and ethical concerns, data integration and interoperability, data models and terminologies, unstructured data reuse, structured data mining, clinical practice and research integration, and examples of clinical data reuse (quality measurement and learning healthcare systems). Conclusion: Reuse of clinical data is a fast-growing field recognized as essential to realize the potentials for high quality healthcare, improved healthcare management, reduced healthcare costs, population health management, and effective clinical research.

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Evaluating Model-Driven Development for large-scale EHRs through the openEHR approach

Cited by 49 publications

References 36 publications

2016 Year-in-Review of Clinical and Consumer Informatics: Analysis and Visualization of Keywords and Topics

2016 Year-in-Review of Clinical and Consumer Informatics: Analysis and Visualization of Keywords and Topics

Applying openEHR’s Guideline Definition Language to the SITS international stroke treatment registry: a European retrospective observational study

Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress

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